A novel modified differential evolution algorithm for constrained optimization problems

Authors:
Dexuan Zou;Haikuan Liu;Liqun Gao;Steven Li
Affiliations:
School of Electrical Engineering and Automation, Xuzhou Normal University, Xuzhou, Jiangsu 221116, PR China;School of Electrical Engineering and Automation, Xuzhou Normal University, Xuzhou, Jiangsu 221116, PR China;School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning 110004, PR China;Division of Business University of South Australia GPO Box 2471, Adelaide, SA 5001, Australia
Venue:
Computers & Mathematics with Applications
Year:
2011

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Abstract

A novel modified differential evolution algorithm (NMDE) is proposed to solve constrained optimization problems in this paper. The NMDE algorithm modifies scale factor and crossover rate using an adaptive strategy. For any solution, if it is at a standstill, its own scale factor and crossover rate will be adjusted in terms of the information of all successful solutions. We can obtain satisfactory feasible solutions for constrained optimization problems by combining the NMDE algorithm and a common penalty function method. Experimental results show that the proposed algorithm can yield better solutions than those reported in the literature for most problems, and it can be an efficient alternative to solving constrained optimization problems.